EnterpriseDB (EDB) has launched the Postgres Vitality Index, a framework measuring commercial contributions to PostgreSQL as the database becomes foundational to enterprise AI. The index reveals EDB leads with over 30% of key contributions, followed by AWS, Microsoft, Fujitsu, and others. The index evaluates 12 factors across core contributions, ecosystem development, and community investment. PostgreSQL is now the strategic choice for over 55% of developers worldwide, prompting major technology companies to increase investment. EDB also announced its EDB Postgres AI platform, designed to address data sovereignty and governance challenges in enterprise AI deployments. The platform unifies transactional, analytical, and AI workloads whilst offering hybrid-by-design architecture. EDB has authored a definitive guide to building AI platforms with PostgreSQL, which will be distributed to 25,000 attendees at NVIDIA's GTC event.

EDB named Sustainability Innovation of the Year winner at the CRN 2026 Sustainability in Tech Awards. PR Newswire Today at 5:43am PST PR Newswire WILMINGTON, Del., Feb. 25, 2026 As energy emerges as the defining constraint of the AI era, recognition affirms EnterpriseDB's leadership in sovereign data infrastructure that enables enterprises to scale compute while reducing data center emissions by up to 87%. WILMINGTON, Del., Feb. 25, 2026 /PRNewswire/ - EnterpriseDB (EDB), the leading sovereign AI and data company, today announced that it has been named Sustainability Innovation of the Year (Support) winner at CRN's 2026 Sustainability in Tech Summit & Awards. Recognized alongside other 2026 award winners including Lenovo and Vodafone, EDB's win underscores a fundamental market shift: Energy is no longer a background line item but the defining constraint for AI success. Global data center investment is projected to exceed $3 trillion over the next five years to meet AI-driven demand. Today, 83% of enterprises now rank power efficiency among their top three drivers for rethinking data center architectures. EDB's sovereign data and AI platform, EDB Postgres(R) AI (EDB PG AI), is designed to address this challenge at the architecture level. Independent analysis validates that organizations using EDB PG AI can reduce core usage by up to 94% in high-availability applications, while reducing modeled application-related data center emissions by up to 87% in certain customer scenarios. "In the age of AI, data centers are the new factories, and energy is the new constraint," said Kevin Dallas, CEO of EDB. "You can't optimize what you don't control. By modernizing replication and unifying workloads, we allow organizations to eliminate the 'idle waste' that quietly drains the grid. Only when you have total sovereignty over your compute and data can you break these energy constraints and scale AI responsibly." Enabling a new architecture of efficiency An independent analysis validated by Incendium Consulting, a sustainability advisory firm, examined deployments across three of the world's largest financial services enterprises, collectively operating more than 120 data centers globally. Key findings from the report, Optimizing the Core, include: * Tier 1 application impact: Core requirements were reduced by up to 94% in modeled high-availability application environments * Real-world reduction: For one global enterprise, the analysis estimates over 10,000 metric tons in avoided emissions annually for applications in scope. * Operational gains: Architectural consolidation and reduced core requirements lower infrastructure costs and improve overall total cost of ownership (TCO). Empowering channel partners: Sustainability as performance For EDB's global partner network, these efficiency gains offer a pragmatic way to help customers reclaim power capacity and budget for new AI initiatives. By delivering sovereign AI-ready architecture, EDB enables partners to address two critical challenges in the modern data center: power availability and TCO. In parallel, EDB holds itself to the same rigorous standards aligned with the commitments it supports for its customers. The company's own emissions reduction targets are validated by the Science Based Targets initiative (SBTi), aligning its decarbonization plans with the strictest global frameworks followed by many Fortune 500 organizations. EDB Postgres(R) AI (EDB PG AI) is the first open, enterprise-grade sovereign data and AI platform - secure, compliant, and scalable, on premises and across clouds. Built on Postgres, the world's leading database, EDB PG AI unifies transactional, analytical, and AI workloads, enabling organizations to operationalize their data and LLMs while maintaining control over sovereign environments. EDB PG AI is supported by a global partner network and delivers up to 99.999% availability as well as hybrid management and a built-in AI factory. As one of the most active contributors to the PostgreSQL project, EDB is deeply invested in the vitality of the global community. To learn more, visit www.enterprisedb.com. EnterpriseDB and EDB are registered trademarks of EnterpriseDB Corporation. Postgres and PostgreSQL are registered trademarks of the PostgreSQL Community Association of Canada and used with their permission. All other trademarks are owned by their respective owners. SOURCE EnterpriseDB This is a paid placement. For further inquiries, please contact PR Newswire directly.

EnterpriseDB updates WarehousePG with features that fuel AI. The PostgreSQL database specialist's data warehouse update targets AI development by adding predictable pricing, real-time data processing and improved governance capabilities. EnterpriseDB on Tuesday unveiled new EDB Postgres AI for WarehousePG features, including per-core pricing to help users control AI development costs and streaming data capabilities aimed at feeding AI applications with real-time data. Launched in April, WarehousePG is an open-source PostgreSQL data warehouse based on the Greenplum Database project's source code. WarehousePG is part of EDB Postgres AI, a database platform introduced in May 2024 that unifies data management, analytics and AI. PostgreSQL is a relational database system known for its flexibility and versatility. Beyond traditional relational database capabilities, PostgreSQL supports geospatial, JSON, time series and vector database workloads. A PostgreSQL data warehouse acts as a centralized repository for data that is fed to analytics and AI workloads. In addition to streaming data and a predictable pricing model, new WarehousePG features include upgraded data observability and data sovereignty capabilities with flexible deployment on any cloud, on-premises and across regions. The WarehousePG update provides EnterpriseDB users with some of the requisite capabilities for AI development and is therefore a valuable addition, according to analyst Carl Olofson, who recently founded DBMSGuru after 28 years at IDC. "From an AI perspective, providing real-time streaming and enhanced observability are significant updates, since they put the resulting package into competition with other leading commercial data warehouse relational database offerings for AI," he said. "The emphasis on sovereignty is also important as it addresses a leading issue in the application of AI to data having international sources." Based in Wilmington, Del., EnterpriseDB competes with database vendors, such as MongoDB and MariaDB, as well as hyperscalers that provide PostgreSQL databases, including AWS, Google, Microsoft and Oracle. WarehousePG upgrade. Many enterprises are increasing their investments in AI initiatives due to advances in AI technology that started with OpenAI's November 2022 launch of ChatGPT. Applications such as generative AI (GenAI) chatbots and AI agents simplify data exploration and analysis so workers can make informed decisions. They also help organizations to automate certain tasks and processes, improving overall efficiency. However, building chatbots and agents can be expensive. Chatbots and agents depend on large volumes of high-quality data to perform properly, far more than is required to inform traditional analytics tools, such as reports and dashboards. Ingesting, integrating, preparing and monitoring data for AI is therefore more time-consuming than for traditional analytics. It also demands significantly more compute power - both for storage and running workloads - than analytics tools. As a result, enterprises are spending far more to develop AI tools than in building analytics applications. To help customers manage AI-related spending, numerous vendors have made cost control a focal point. For example, AWS targeted cost control with data management features unveiled during its re:Invent user conference in early December. Similarly, database vendors including Aerospike and Neo4j have added performance improvements aimed at helping customers lower their spending. EnterpriseDB targets cost control by charging WarehousePG users on a per-core pricing model rather than consumption-based billing. Per-core pricing charges customers based on the number of CPU cores used for their WarehousePG deployment, which fixes the cost. Consumption-based pricing models fluctuates based on usage, which sometimes far exceeds expectations. Given that the cost of AI development is a concern for many enterprises, EnterpriseDB's per-core pricing for WarehousePG is significant, according to Kevin Petrie, an analyst at BARC U.S. "AI adopters will appreciate the per-core pricing as an alternative to consumption-based billing," he said. "BARC research shows that software is the biggest contributor to cost overruns with AI projects, and this mitigates that risk." In addition to per-core pricing, EnterpriseDB's addition of data streaming capabilities in WarehousePG is valuable, Petrie continued. Stream processing is the continuous, high-speed movement of data from its source, through a data streaming platform, to applications and is a key feature of agentic AI pipelines, enabling agents to act on real-time information. "We see huge demand for data streaming given the low latency of modern workloads," Petrie said. "Many of the most popular AI use cases - such as fraud detection, preventive maintenance and price optimization - can benefit from EnterpriseDB's support for data streaming." Olofson similarly highlighted WarehousePG's streaming capabilities. "If you want to incorporate AI processing into a workflow, and not just use it for end-user query, the streaming support is critical," he said. Beyond per-core pricing and new data streaming capabilities, EnterpriseDB's WarehousePG update includes the following: * An AI-ready architecture that includes stream processing, native vector search and storage capabilities and in-database machine learning with Python and MADlib. * Flexible deployment on any cloud or on premises, across regions. * Data governance capabilities, including data observability to monitor anomalies and changes that can affect AI outputs. While predictable pricing and streaming capabilities stand out, the WarehousePG update was driven by conversations with customers, according to Quais Taraki, EnterpriseDB's chief technology officer. "This update was decisively customer-driven," he said. In addition, EnterpriseDB market research that showed95% of enterprises plan to unify data and AI over the next three years, and that data sovereignty is a point of emphasis, played a role in this release, Taraki continued. "These capabilities were prioritized to reflect that reality," he said. Looking ahead. With the latest WarehousePG update now available, EnterpriseDB will focus on improving the interoperability of the EDB Postgres AI platform in 2026, according to Taraki. Database platforms provide a broad range of capabilities. But to best serve customers building AI and analytics applications, integrations that enable easy connections with external platforms are valuable. "In 2026, a key focus will be deepening interoperability across the AI and analytics ecosystem," Taraki said. "That means stronger business continuity and security, tighter integration with open data and AI frameworks, and fewer operational barriers for customers modernizing analytics workloads on Postgres." EnterpriseDB's emphasis on interoperability is wise, according to Olofson, who noted that more partnerships and integrations help position the vendor's database offerings within broader analytics and AI ecosystems. "EnterpriseDB's platform is quite competitive on its own, but when businesses look to use it in a complex data management environment, especially one supporting AI, they need a constellation of other technologies as well," he said. "The key for EnterpriseDB is in partnering with technology suppliers and consultants that can cast the [EnterpriseDB PostgreSQL] offerings into a context of business solutions." Eric Avidon is a senior news writer for Informa TechTarget and a journalist with more than 25 years of experience. He covers analytics and data management.